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- Supply Chain Management in the Construction Industry: The Ultimate Guide
- What is supply chain management in the construction industry? First of all, what is supply chain management? Supply chain management (SCM) is the oversight of materials, information and finances throughout the process, from suppliers to manufacturers, wholesalers, retailers, ultimately to the consumer. The main processes in the supply chain include product flow, information flow and capital flow. SCM involves coordinating and integrating these processes within and between enterprises. It is one of the most complex areas of the construction value chain. The supply chain management industry is currently in a high-growth phase, driven by innovations such as artificial intelligence, data analytics, and machine learning. It is estimated that its global market value will be US$23 million by 2023 and is expected to grow by 11.2% from 2024 to 2030. In the construction industry, supply chain management (SCM)
- AI 256 2024-04-18 16:01:27
- Meta unlimited long text large model is here: only 7B parameters, open source
- After Google, Meta also comes to roll infinitely long contexts. The quadratic complexity and weak length extrapolation of Transformers limits their ability to scale to long sequences. Although quadratic solutions such as linear attention and state space models exist, from past experience, they suffer from pre-training efficiency. and poor performance on downstream task accuracy. Recently, Infini-Transformer proposed by Google has attracted people's attention by introducing an effective method to extend Transformer-based large language models (LLM) to infinitely long inputs without increasing storage and computing requirements. Almost at the same time, Meta also proposed an infinitely long text technology. Paper address: https://arxi
- AI 885 2024-04-18 15:40:01
- Everyone can become an AI developer! Robin Li brings three major AI development tools
- Emerging as the brightest star in the technology field in early 2023, it demonstrates the huge potential of Kai AI technology to transform the economy and society. After more than a year of technological breakthroughs and market verification, entering 2024, the huge value of large models has been recognized by mainstream countries, and mainstream technology companies have made plans. Countries such as the United States and China are in the future of leading the development of the large model industry. Among domestic technology companies, Baidu was the first to release Wenxin's large model and has achieved extraordinary results. At the Create2024 Baidu AI Developer Conference held today, Robin Li, founder, chairman and CEO of Baidu, revealed in his keynote speech that the number of Wenxin Yiyan users exceeded 200 million, and the Wenxin Big Model has become China's leading and most widely used model. Extensive AI base models. At the same time, Robin Li
- AI 671 2024-04-18 15:40:01
- How does artificial intelligence bring revolutionary changes to smartphones?
- Artificial intelligence (AI) has always been considered a core functional technology in various fields, and smartphones are a typical example of the possibilities and energy of the new generation. Artificial intelligence is no longer just a matter of matching human interface levels, but of making devices perform better than ever before. This article will discuss the artificial intelligence capabilities of smartphones and how it will revolutionize modern smartphones. Personalized User Experience Today, smartphones can recommend more frequent updates, content suggestions, and notifications with the help of smart artificial intelligence algorithms that leverage the user’s activities, taste preferences, and trend observations. New-generation mobile technologies such as personalized home screens, artificial intelligence (AI) voice assistants, and virtual reality (VR) applications only solve the problem of smartphone users.
- AI 364 2024-04-18 14:43:14
- New direction of digital twin application: analyzing infant development
- Research led by the University of Chicago shows that "digital twins" driven by AI technology can model the baby's microbiome to predict possible neurodevelopmental problems that may occur later in the baby's growth. Using very early gut microbiome-related data from fecal samples of premature infants, the digital twin was able to very accurately predict their later microbiome composition and corresponding neurodevelopmental defects. "We just looked at a snapshot of the microbiome and analyzed different levels of each type of bacteria," lead author Ishanu Chattopadhyay of the University of Chicago said in a statement. Quick conclusion: This is because the microbiome continues to change and mature during early childhood."
- AI 738 2024-04-18 11:10:18
- Thoughts and practice on assisted generation of B-end front-end code under large models
- 1. Code specifications during background reconstruction work: During the B-end front-end development process, developers will always face the pain point of repeated development. The element modules of many CRUD pages are basically similar, but they still need to be developed manually, and time is spent on simple element construction. This reduces the development efficiency of business requirements. At the same time, because the coding styles of different developers are inconsistent, it makes it more expensive for others to get started during iterations. AI replaces simple brainpower: With the continuous development of large AI models, it has simple understanding capabilities and can convert language into instructions. General instructions for building basic pages can meet the needs of daily basic page building and improve the efficiency of business development in general scenarios. 2. Generate link list. B-side page lists, forms, and details can all be generated. Links can be roughly divided into the following categories:
- AI 906 2024-04-18 09:30:15
- Sweep 99 sub-missions with MoE! Zhejiang University and others proposed a new general robot strategy GeRM
- Multi-task robot learning is of great significance in coping with diverse and complex scenarios. However, current methods are limited by performance issues and difficulties in collecting training datasets. This paper proposes GeRM (Generic Robot Model), where researchers leverage offline reinforcement learning to optimize data utilization strategies, learning from demonstrations and suboptimal data, thereby transcending the limitations of human demonstrations. Authors: Song Wenxuan, Zhao Han, Ding Pengxiang, Cui Can, Lu Shangke, Fan Yaning, Wang Donglin Unit: West Lake University, Zhejiang University Paper address: https://arxiv.org/abs/2403.13358 Project address: https://songwxuan.github .io/GeRM/ will be based on Tra
- AI 527 2024-04-17 23:40:24
- A new breakthrough was made in the minimum cut problem of undirected graphs, and Google research won the SODA 2024 Best Paper Award
- Google blog released new research to solve the minimum cut problem of undirected graphs. In 1996, American computer scientist David R Karger and other researchers proposed a surprising random algorithm Karger algorithm in the paper "A new approach to the minimum cut problem". It is very important in theoretical computer science and is especially suitable for approximate minimum cut problems on large-scale graphs. Karger's algorithm can find a minimum cut point in a graph in time O(mlog^3n). They call this time nearly linear time, which means linear multiplication by a polylogarithmic factor. In a blog just updated by Google, they introduced a previously published paper "Det
- AI 700 2024-04-17 21:58:01
- Bots now account for nearly half of global internet traffic
- According to the latest report research, nearly half (49.6%) of Internet traffic will come from robots in 2023. This was a 2% increase from the previous year and the highest level reported since automated traffic began monitoring in 2013. The proportion of network traffic related to malicious bots will increase for the fifth consecutive year to 32% in 2023, up from 30.2% in 2022. Meanwhile, traffic from human users dropped to 50.4%. Automated traffic costs organizations billions of dollars every year due to attacks on websites, APIs, and applications. Robots are one of the most prevalent and growing threats facing every industry. From simple web scraping to malicious account takeovers, spam, and denial of service, bots can degrade online services and require additional work on infrastructure.
- AI 848 2024-04-17 20:43:32
- OWASP releases large language model network security and governance checklist
- The biggest risk currently faced by artificial intelligence technology is that the development and application speed of large language models (LLM) and generative artificial intelligence technology have far exceeded the speed of security and governance. Use of generative AI and large language model products from companies like OpenAI, Anthropic, Google, and Microsoft is growing exponentially. At the same time, open source large language model solutions are also growing rapidly. Open source artificial intelligence communities such as HuggingFace provide a large number of open source models, data sets and AI applications. In order to promote the development of artificial intelligence, industry organizations such as OWASP, OpenSSF, and CISA are actively developing and providing key assets for artificial intelligence security and governance, such as OWASPAIExchange,
- AI 955 2024-04-17 19:31:01
- EEG synthesis of natural speech! LeCun forwards new results of Nature sub-journal, and the code is open source
- The latest progress in brain-computer interfaces was published in the Nature sub-journal, and LeCun, one of the three giants of deep learning, also forwarded it. This time, neural signals are used for speech synthesis to help people with aphasia due to neurological defects regain the ability to communicate. It is reported that a research team from New York University has developed a new type of differentiable speech synthesizer that can use a lightweight convolutional neural network to encode speech into a series of interpretable speech parameters (such as pitch, loudness, formant frequency, etc. ), and resynthesize the speech through a differentiable speech synthesizer. By mapping neural signals to these speech parameters, the researchers built a neural speech decoding system that is highly interpretable and applicable to small-data-size situations, producing natural-sounding speech. 48 researchers collected a total of
- AI 567 2024-04-17 19:01:27
- Build a generative AI innovation security system, Amazon's chief security officer teaches you three tips
- Amazon Cloud Technology has millions of customers around the world and tracks billions of events every day, allowing Amazon Cloud Technology to detect more security threats. In 2019, Amazon Cloud Technology Chief Security Officer Steve Schmidt officially announced the launch of Amazon Cloud Technology re:Inforce, the first conference focusing on cloud security issues. The conference has now been held for five times and has become a benchmark for cloud security. In 2010, Steve Schmidt joined Amazon and served as the chief information security officer of Amazon Cloud Technology for 12 years. He has served as the chief security officer of Amazon since 2022. Recently, he was interviewed by The Wall Street Journal about enterprise security in the age of generative AI. SteveSchmidt said the security team
- AI 353 2024-04-17 18:40:02
- nuScenes' latest SOTA | SparseAD: Sparse query helps efficient end-to-end autonomous driving!
- Written in front & starting point The end-to-end paradigm uses a unified framework to achieve multi-tasking in autonomous driving systems. Despite the simplicity and clarity of this paradigm, the performance of end-to-end autonomous driving methods on subtasks still lags far behind single-task methods. At the same time, the dense bird's-eye view (BEV) features widely used in previous end-to-end methods make it difficult to scale to more modalities or tasks. A sparse search-centric end-to-end autonomous driving paradigm (SparseAD) is proposed here, in which sparse search fully represents the entire driving scenario, including space, time, and tasks, without any dense BEV representation. Specifically, a unified sparse architecture is designed for task awareness including detection, tracking, and online mapping. In addition, heavy
- AI 588 2024-04-17 18:22:16
- Tsinghua team launches new platform: using decentralized AI to break computing power shortage
- Recently, a piece of data points out the astonishing growth in the demand for computing power in the AI field - according to estimates by industry experts, the Sora launched by OpenAI requires approximately 4,200-10,500 NVIDIA H100s for one month of training, and when the model is generated After the inference stage, the computational cost will quickly exceed the training stage. If this trend continues, it may be difficult for GPU supply to meet the continued demand for large models. However, there has been a new trend overseas recently, which may provide new solutions to the upcoming "computing power shortage" - decentralized AI. Three weeks ago, on March 23, StabilityAI suddenly issued an announcement announcing the resignation of company CEO Emad Mostaque. EmadMo
- AI 512 2024-04-17 18:16:14
- Generative AI brings real-time supply chains closer to reality
- Generative artificial intelligence is affecting or expected to affect many industries, and the time for supply chain network transformation is ripe. Generative AI promises to significantly facilitate real-time interactions and information in the supply chain, from planning to procurement, manufacturing and fulfillment. The impact on productivity of all these processes is significant. A new study from Accenture calculates that all working hours of end-to-end supply chain activities of more than 40% of enterprises (43%) may be affected by production artificial intelligence. In addition, 29% of the working time in the entire supply chain can be automated through production AI, while 14% of the working time in the entire supply chain can be significantly increased through production AI. This emerging technology has the potential to impact the entire supply chain, from design and planning, to sourcing and manufacturing, to fulfillment.
- AI 1035 2024-04-17 17:25:01
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